activity
20242026
most citedOn the Rigour of Scientific Writing: Criteria, Analysis, and Insights

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SD2026

The Achilles' Heel of Angular Margins: A Chebyshev Polynomial Fix for Speaker Verification

Yang Wang, Yiqi Liu, Chenghao Xiao +1

Angular margin losses, such as AAM-Softmax, have become the de facto in speaker and face verification. Their success hinges on directly manipulating the angle between features and…

cs.CL2026

RIGOURATE: Quantifying Scientific Exaggeration with Evidence-Aligned Claim Evaluation

Joseph James, Chenghao Xiao, Yucheng Li +2

Scientific rigour tends to be sidelined in favour of bold statements, leading authors to overstate claims beyond what their results support. We present RIGOURATE, a two-stage multi…

cs.CL2025

Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth

Yang Wang, Chenghao Xiao, Chia-Yi Hsiao +4

We introduce Drivelology, a unique linguistic phenomenon characterised as "nonsense with depth" - utterances that are syntactically coherent yet pragmatically paradoxical, emotiona…

cs.CL2025

Adversarial Defence without Adversarial Defence: Enhancing Language Model Robustness via Instance-level Principal Component Removal

Yang Wang, Chenghao Xiao, Yizhi Li +3

Pre-trained language models (PLMs) have driven substantial progress in natural language processing but remain vulnerable to adversarial attacks, raising concerns about their robust…

cs.CL2025

Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts

Hanhua Hong, Chenghao Xiao, Yang Wang +3

Evaluating natural language generation systems is challenging due to the diversity of valid outputs. While human evaluation is the gold standard, it suffers from inconsistencies, l…

cs.CL20242 cited

On the Rigour of Scientific Writing: Criteria, Analysis, and Insights

Joseph James, Chenghao Xiao, Yucheng Li +1

Rigour is crucial for scientific research as it ensures the reproducibility and validity of results and findings. Despite its importance, little work exists on modelling rigour com…